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Jayeetra Bhattacharjee
Mid-level AI/ML Engineer specializing in LLMs, NLP, and analytics automation
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About
AI/ML Engineer (TCS) who built and deployed a production LLM-powered audit transaction validation service to reduce manual review of unstructured transaction records and comments. Implemented a LangChain/Python pipeline for extraction/normalization and discrepancy detection, with strong production reliability practices (decision logging, dashboards, labeled eval sets) and a human-in-the-loop auditor feedback loop to improve precision/recall under strict data-sensitivity and near-real-time constraints.
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Key Strengths
- Built and deployed a production LLM-based audit transaction validation system
- Strong handling of messy/unstructured data via preprocessing, validation, and schema-change resilience
- Designed extraction + normalization pipeline using regex and NLP/NER
- Implemented discrepancy detection using hybrid ML + rules and anomaly/outlier detection
- Established measurable evaluation with labeled historical data plus production logging and dashboards
- Closed-loop improvement using auditor feedback to tune prompts/rules and manage precision/recall tradeoffs
- Pragmatic model selection under constraints (data sensitivity, latency, precision), including self-hosted lightweight LLMs and structured JSON outputs
- Automated CI/CD release pipeline with GitLab CI (Docker build, unit tests, evals, staged deploys with approvals)
- Effective collaboration with non-technical stakeholders through demos, targeted questions, and business-metric-driven updates
Reference Highlights
- Excellent cross-team collaboration
- Effective with non-technical stakeholders
- Organized and proactive communicator
- Plans and prepares presentations in advance
- Delegates responsibilities to best-suited team members
- Contributed to production AI/LLM product deliveries
- Successfully shipped LLM-based product to production
- Strong performance collaborating across teams
- Effective at presenting working prototypes to cross-functional teams
- Able to explain complex technical concepts clearly
- Uses analogies to make technical topics understandable
- Focus on operational efficiency and automation
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